1,720,995 research outputs found
Multivariate comonotonicity
No full textIn this paper we consider several multivariate extensions of comonotonicity. We show that naive extensions do not enjoy some of the main properties of the univariate concept. In order to have these properties, more structures are needed than in the univariate case
A simple and fast method for Named Entity context extraction from patents
No full textThe process of extracting relevant technical information from patents or technical literature is as valuable as it is challenging. It deals with highly relevant information extraction from a corpus of documents with particular structure, and a mix of technical and legal jargon. Patents are the wider free source of technical information where homogeneous entities can be found. From a technical perspective the approaches refer to Named Entity Recognition (NER) and make use of Machine Learning techniques for Natural Language Processing (NLP). However, due to the large amount of data, to the complexity of the lexicon, the peculiarity of the structure and the scarcity of the examples to be used to feed the machine learning system, new approaches should be studied. NER methods are increasing their performances in many contexts, but a gap still exists when dealing with technical documentation. The aim of this work is to create an automatic training sets for NER systems by exploiting the nature and structure of patents, an open and massive source of technical documentation. In particular, we focus on collecting the context where users of the invention appear within patents. We then measure to which extent we achieve our goal and discuss how much our method is generalizable to other entities and documents
The Invalsi Benchmarks: measuring Linguistic and Mathematical understanding of Large Language Models in Italian
No full textWhile Italian is a high-resource language, there are few Italian-native benchmarks to evaluate generative Large Language Models (LLMs) in this language. This work presents three new benchmarks: Invalsi MATE to evaluate models performance on mathematical understanding in Italian, Invalsi ITA to evaluate language under standing in Italian and Olimpiadi MATE for more complex mathematical understanding. The first two benchmarks are based on the Invalsi tests, which are administered to students of age between 6 and 18 within the Italian school system and have been validated by several experts in teaching and pedagogy, the third one comes from the Italian highschool math Olympics. We evaluate 10 powerful language models on these benchmarks and we find that they are bound by 71% accuracy on Invalsi MATE, achieved by Llama 3.1 70b instruct and by 88% on Invalsi ITA. For both Invalsi MATE and Invalsi ITA we compare LLMs with the average performance of Italian students to show that Llama 3.1 is the only one to outperform them on Invalsi MATE while most models do so on Invalsi ITA, we then show that Olimpiadi MATE is more challenging than Invalsi MATE and the highest accuracy, achieved by Llama 3.1 405b instruct accuracy is 45%
Die Copulae fanden mich ... Interview mit Paul Embrechts
No full textPaul Embrechts ist Professor für Mathematik an der ETH Zürich, spezialisiert auf Versicherungsmathematik und Quantitatives Risk Management. Während seiner akademischen Karriere forschte und lehrte er unter anderem an den Universitäten Leuven, Limburg und London (Imperial College). Paul Embrechts nimmt Gastprofessuren an verschiedenen Universitäten wahr, darunter der Scuola Normale in Pisa (Cattedra Galileiana), der London School of Economics (Centennial Professor of Finance), der Universität Wien, Paris (Panthéon-Sorbonne), der National University of Singapur und der Kyoto University. Er war im Jahr 2014 Gast am Oxford-Man Institute der Universität Oxford und hat Ehrendoktorwürden der University of Waterloo, Heriot-Watt University Edinburgh, und der Université Catholique de Louvain. Er ist gewähltes Mitglied des Instituts für mathematische Statistik und der American Statistical Association, Ehrenmitglied des Instituts und der Fakultät für Aktuare, Versicherungsmathematiker- SAA, Mitglied Honoris Causa der belgischen Institute of Actuaries und ist in der Redaktion zahlreicher wissenschaftlicher Journals
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
B4DS @ PRELEARN: Ensemble method for prerequisite learning
No full textIn this paper we describe the methodologies we proposed to tackle the EVALITA 2020 shared task PRELEARN. We propose both a methodology based on gated recurrent units as well as one using more classical word embeddings together with ensemble methods. Our goal in choosing these approaches, is twofold, on one side we wish to see how much of the prerequisite information is present within the pages themselves. On the other we would like to compare how much using the information from the rest of Wikipedia can help in identifying this type of relation. This second approach is particularly useful in terms of extension to new entities close to the one in the corpus provided for the task but not actually present in it. With this methodologies we reached second position in the challenge
Activated sludge biodegradation test as a screening method to evaluate persistence of pesticides in soil
No full textREVERINO: REgesta generation VERsus latIN summarizatiOn
Full text linkIn this work we introduce the REVERINO dataset, a collection of 4533 pairs of Latin regesta with their respective full text medieval pontifical document extracted from two collections, Epistolae saeculi XIII e regestis pontificum Romanorum selectae. (1216-1268) and Les Registres de Gregoire IX (1227/41). We describe the pipeline used to extract the text from the images of the printed pages and we make high level analysis of the corpus. After developing REVERINO we use it as a benchmark to test the ability of Large Language Models (LLMs) to generate the regestum of a given Latin text. We test 3 LLMs among the best performing ones, GPT-4o, Llama 3.1 70b and Llama 3.1 405b and find that GPT-4o is the best at generating text in Latin. Interestingly, we also find that for Llama models it can be beneficial to first generate a text in English and then translate it in Latin to write better regesta
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
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